Geographic Information Sciences Commons^™

A Study On Modelling Spatial-Temporal Human Mobility Patterns For Improving Personalized Weather Warning, Yue Xu

Masters Theses

Understanding human mobility patterns is important for severe weather warning since these patterns can help identify where people are in time and in space when flash floods, tornados, high winds and hurricanes are occurring or are predicted to occur. A GIS (Geographic Information Science) data model was proposed to describe the spatial-temporal human activity. Based on this model, a metric was designed to represent the spatial-temporal activity intensity of human mobility, and an index was generated to quantitatively describe the change in human activities. By analyzing high-resolution human mobility data, the paper verified that human daily mobility patterns could be …